Linguistic Consensus Models based on a Fuzzy Ontology

Pérez, Ignacio Javier; Wikstrm, R.; Mezei, József; Carlsson, Christer; Anaya, Karina; Herrera‐Viedma, Enrique

doi:10.1016/j.procs.2013.05.064

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…Although research in the linguistic modelling field is not a trendy topic in this moment, there is plenty of articles these days that use linguistic modelling in [12,13] use linguistic modelling in order to deal with vague information. Linguistic modelling has also been previously used to improve ontologies as readers can see in references [14][15][16].…”

Section: Linguistic Modellingmentioning

confidence: 99%

Designing a Decision Support System for Recommending Smartphones Using Fuzzy Ontologies

Morente-Molinera

Pérez

Wikström

et al. 2015

Advances in Intelligent Systems and Computing

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Abstract. Nowadays, smartphones have become indispensable items for everybody. Thanks to them, people can communicate and access Internet at any time regardless of where they are located. New smartphones belonging to a high amount of labels and with different features and prices keep appearing constantly in the market. This way, there is a need of tools that help buyers to select and buy the smartphone that better fits their necessities. In this article, a decision support system build over a fuzzy ontology has been designed in order to help people to select the perfect smartphone for them. Linguistic labels are used in order to provide the buyer with a comfortable way of expressing himself/herself.

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Section: Linguistic Modellingmentioning

confidence: 99%

Designing a Decision Support System for Recommending Smartphones Using Fuzzy Ontologies

Morente-Molinera

Pérez

Wikström

et al. 2015

Advances in Intelligent Systems and Computing

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“…Calegari constructed a framework of fuzzy ontology with fuzzy description logic and fuzzy OWL language [4]. Pérez proposed a new linguistic extension of a consensus model to deal with the psychology of negotiation by using fuzzy ontology for improving group decision more precise and realistic [5].…”

Section: Introductionmentioning

confidence: 99%

Grey Ontology Model for Expert Knowledge Representation

Shen¹,

Zhao²

2016

Proceedings of the 2016 International Conference on Electrical, Mechanical and Industrial Engineering

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In order to improve the knowledge representation of ontology for dealing with grey uncertainty, grey ontology is proposed. Firstly, grey systems theory, probability theory and fuzzy theory are compared. Secondly, interval grey number and its calculation are introduced. At last, the model grey ontology is proposed and the main elements are also analyzed. It shows that grey ontology can overcome the limitation of other ontologies to describe the expert knowledge with grey uncertainty.

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